Overview

Brought to you by YData

Dataset statistics

Number of variables	22
Number of observations	199
Missing cells	730
Missing cells (%)	16.7%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	132.7 KiB
Average record size in memory	683.0 B

Variable types

Text	2
DateTime	1
Categorical	11
Numeric	8

Alerts

`cluster_k_4` has constant value "2"	Constant
`Estado` is highly overall correlated with `cant_MontoLimite`	High correlation
`anio_preinscripcion` is highly overall correlated with `antiguedad`	High correlation
`antiguedad` is highly overall correlated with `anio_preinscripcion`	High correlation
`cant_Apoderado` is highly overall correlated with `cant_MontoLimite` and 2 other fields	High correlation
`cant_MontoLimite` is highly overall correlated with `Estado` and 7 other fields	High correlation
`cant_antecedentes` is highly overall correlated with `cant_MontoLimite` and 1 other fields	High correlation
`cant_apercibimientos` is highly overall correlated with `cant_MontoLimite` and 1 other fields	High correlation
`cant_autenticado` is highly overall correlated with `cant_sinMontoLimite`	High correlation
`cant_noAutenticado` is highly overall correlated with `cant_Apoderado` and 3 other fields	High correlation
`cant_procesos_adjudicado` is highly overall correlated with `monto_total_adjudicado`	High correlation
`cant_representante` is highly overall correlated with `cant_MontoLimite`	High correlation
`cant_sinMontoLimite` is highly overall correlated with `cant_Apoderado` and 2 other fields	High correlation
`cant_suspensiones` is highly overall correlated with `cant_MontoLimite` and 2 other fields	High correlation
`monto_total_adjudicado` is highly overall correlated with `cant_MontoLimite` and 1 other fields	High correlation
`total_articulos_provee` is highly overall correlated with `cant_MontoLimite`	High correlation
`Estado` is highly imbalanced (71.1%)	Imbalance
`provincia` is highly imbalanced (51.8%)	Imbalance
`cant_apercibimientos` is highly imbalanced (74.6%)	Imbalance
`cant_representante` is highly imbalanced (58.5%)	Imbalance
`cant_autenticado` is highly imbalanced (66.2%)	Imbalance
`cant_noAutenticado` is highly imbalanced (50.8%)	Imbalance
`cant_socios` has 45 (22.6%) missing values	Missing
`cant_apercibimientos` has 58 (29.1%) missing values	Missing
`cant_suspensiones` has 109 (54.8%) missing values	Missing
`cant_antecedentes` has 3 (1.5%) missing values	Missing
`cant_Apoderado` has 56 (28.1%) missing values	Missing
`cant_representante` has 104 (52.3%) missing values	Missing
`cant_noAutenticado` has 159 (79.9%) missing values	Missing
`cant_MontoLimite` has 193 (97.0%) missing values	Missing
`CUIT` has unique values	Unique

Reproduction

Analysis started	2025-06-24 13:32:42.087666
Analysis finished	2025-06-24 13:32:49.238258
Duration	7.15 seconds
Software version	ydata-profiling vv4.16.1
Download configuration	config.json

CUIT
Text

Unique

Distinct	199
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	14.8 KiB

Length

Max length	12
Median length	11
Mean length	10.994975
Min length	9

Characters and Unicode

Total characters	2188
Distinct characters	11
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	199 ?
Unique (%)	100.0%

Sample

1st row	30711500363
2nd row	30590151013
3rd row	30678561165
4th row	30591267759
5th row	30702024834

Value	Count	Frequency (%)
30711500363	1	0.5%
30590151013	1	0.5%
30678561165	1	0.5%
30591267759	1	0.5%
30702024834	1	0.5%
30623295946	1	0.5%
30673249902	1	0.5%
30714236888	1	0.5%
30710362218	1	0.5%
30710828608	1	0.5%
Other values (189)	189	95.0%

Most occurring characters

Value	Count	Frequency (%)
0	358	16.4%
3	307	14.0%
7	251	11.5%
2	240	11.0%
1	202	9.2%
6	198	9.0%
9	172	7.9%
8	163	7.4%
5	158	7.2%
4	138	6.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2188	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	358	16.4%
3	307	14.0%
7	251	11.5%
2	240	11.0%
1	202	9.2%
6	198	9.0%
9	172	7.9%
8	163	7.4%
5	158	7.2%
4	138	6.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2188	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	358	16.4%
3	307	14.0%
7	251	11.5%
2	240	11.0%
1	202	9.2%
6	198	9.0%
9	172	7.9%
8	163	7.4%
5	158	7.2%
4	138	6.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2188	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	358	16.4%
3	307	14.0%
7	251	11.5%
2	240	11.0%
1	202	9.2%
6	198	9.0%
9	172	7.9%
8	163	7.4%
5	158	7.2%
4	138	6.3%

Nombre
Text

Distinct	194
Distinct (%)	97.5%
Missing	0
Missing (%)	0.0%
Memory size	16.6 KiB

Length

Max length	67
Median length	34
Mean length	18.507538
Min length	3

Characters and Unicode

Total characters	3683
Distinct characters	64
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	193 ?
Unique (%)	97.0%

Sample

1st row	LICICOM S.R.L.
2nd row	VIDITEC S.A..
3rd row	NACION SEGUROS S.A.
4th row	ERRE-DE SRL
5th row	Datastar Argentina S.A.

Value	Count	Frequency (%)
s.a	59	10.4%
srl	36	6.3%
s.r.l	21	3.7%
sa	20	3.5%
argentina	13	2.3%
y	11	1.9%
de	10	1.8%
datos	6	1.1%
sin	6	1.1%
s	5	0.9%
Other values (341)	380	67.0%

Most occurring characters

Value	Count	Frequency (%)
	368	10.0%
A	292	7.9%
S	269	7.3%
R	228	6.2%
E	201	5.5%
I	200	5.4%
.	190	5.2%
N	146	4.0%
O	141	3.8%
L	135	3.7%
Other values (54)	1513	41.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3683	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	368	10.0%
A	292	7.9%
S	269	7.3%
R	228	6.2%
E	201	5.5%
I	200	5.4%
.	190	5.2%
N	146	4.0%
O	141	3.8%
L	135	3.7%
Other values (54)	1513	41.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3683	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	368	10.0%
A	292	7.9%
S	269	7.3%
R	228	6.2%
E	201	5.5%
I	200	5.4%
.	190	5.2%
N	146	4.0%
O	141	3.8%
L	135	3.7%
Other values (54)	1513	41.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3683	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	368	10.0%
A	292	7.9%
S	269	7.3%
R	228	6.2%
E	201	5.5%
I	200	5.4%
.	190	5.2%
N	146	4.0%
O	141	3.8%
L	135	3.7%
Other values (54)	1513	41.1%

FechaPreinscripcion
Date

Distinct	156
Distinct (%)	78.4%
Missing	0
Missing (%)	0.0%
Memory size	3.1 KiB

Minimum	2016-02-08 00:00:00
Maximum	2020-10-16 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

Estado
Categorical

High correlation Imbalance

Distinct	8
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	14.8 KiB

Inscripto	174
Desactualizado Por Documentos Vencidos	7
Suspendido	5
Con Solicitud De Baja	4
Desactualizado Por Mantencion Formulario	4
Other values (3)	5

Length

Max length	40
Median length	9
Mean length	11.065327
Min length	9

Characters and Unicode

Total characters	2202
Distinct characters	28
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	1.0%

Sample

1st row	Inscripto
2nd row	Inscripto
3rd row	Inscripto
4th row	Inscripto
5th row	Inscripto

Common Values

Value	Count	Frequency (%)
Inscripto	174	87.4%
Desactualizado Por Documentos Vencidos	7	3.5%
Suspendido	5	2.5%
Con Solicitud De Baja	4	2.0%
Desactualizado Por Mantencion Formulario	4	2.0%
Pre Inscripto	3	1.5%
En Evaluacion	1	0.5%
Desactualizado Por Clase	1	0.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
inscripto	177	70.8%
desactualizado	12	4.8%
por	12	4.8%
documentos	7	2.8%
vencidos	7	2.8%
suspendido	5	2.0%
con	4	1.6%
solicitud	4	1.6%
de	4	1.6%
baja	4	1.6%
Other values (6)	14	5.6%

Most occurring characters

Value	Count	Frequency (%)
o	248	11.3%
i	218	9.9%
n	214	9.7%
c	212	9.6%
s	209	9.5%
t	204	9.3%
r	200	9.1%
p	182	8.3%
I	177	8.0%
a	55	2.5%
Other values (18)	283	12.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2202	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
o	248	11.3%
i	218	9.9%
n	214	9.7%
c	212	9.6%
s	209	9.5%
t	204	9.3%
r	200	9.1%
p	182	8.3%
I	177	8.0%
a	55	2.5%
Other values (18)	283	12.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2202	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
o	248	11.3%
i	218	9.9%
n	214	9.7%
c	212	9.6%
s	209	9.5%
t	204	9.3%
r	200	9.1%
p	182	8.3%
I	177	8.0%
a	55	2.5%
Other values (18)	283	12.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2202	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
o	248	11.3%
i	218	9.9%
n	214	9.7%
c	212	9.6%
s	209	9.5%
t	204	9.3%
r	200	9.1%
p	182	8.3%
I	177	8.0%
a	55	2.5%
Other values (18)	283	12.9%

TipoSocietario
Categorical

Distinct	7
Distinct (%)	3.5%
Missing	0
Missing (%)	0.0%
Memory size	22.0 KiB

Sociedad Anónima	82
Sociedad Responsabilidad Limitada	60
Persona Física	44
Otras Formas Societarias	7
Sociedades De Hecho	3
Other values (2)	3

Length

Max length	40
Median length	33
Mean length	21.256281
Min length	14

Characters and Unicode

Total characters	4230
Distinct characters	33
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.5%

Sample

1st row	Sociedad Responsabilidad Limitada
2nd row	Sociedad Anónima
3rd row	Sociedad Anónima
4th row	Sociedad Responsabilidad Limitada
5th row	Sociedad Anónima

Common Values

Value	Count	Frequency (%)
Sociedad Anónima	82	41.2%
Sociedad Responsabilidad Limitada	60	30.2%
Persona Física	44	22.1%
Otras Formas Societarias	7	3.5%
Sociedades De Hecho	3	1.5%
Persona Jurídica Extranjero Sin Sucursal	2	1.0%
Organismo Publico	1	0.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
sociedad	142	30.0%
anónima	82	17.3%
responsabilidad	60	12.7%
limitada	60	12.7%
persona	46	9.7%
física	44	9.3%
otras	7	1.5%
formas	7	1.5%
societarias	7	1.5%
sociedades	3	0.6%
Other values (8)	16	3.4%

Most occurring characters

Value	Count	Frequency (%)
a	592	14.0%
i	531	12.6%
d	472	11.2%
n	275	6.5%
	275	6.5%
o	272	6.4%
e	269	6.4%
s	237	5.6%
c	204	4.8%
S	156	3.7%
Other values (23)	947	22.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4230	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	592	14.0%
i	531	12.6%
d	472	11.2%
n	275	6.5%
	275	6.5%
o	272	6.4%
e	269	6.4%
s	237	5.6%
c	204	4.8%
S	156	3.7%
Other values (23)	947	22.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4230	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	592	14.0%
i	531	12.6%
d	472	11.2%
n	275	6.5%
	275	6.5%
o	272	6.4%
e	269	6.4%
s	237	5.6%
c	204	4.8%
S	156	3.7%
Other values (23)	947	22.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4230	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	592	14.0%
i	531	12.6%
d	472	11.2%
n	275	6.5%
	275	6.5%
o	272	6.4%
e	269	6.4%
s	237	5.6%
c	204	4.8%
S	156	3.7%
Other values (23)	947	22.4%

anio_preinscripcion
Categorical

High correlation

Distinct	5
Distinct (%)	2.5%
Missing	0
Missing (%)	0.0%
Memory size	13.4 KiB

2016	84
2017	82
2018	22
2019	8
2020	3

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	796
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2016
2nd row	2016
3rd row	2016
4th row	2016
5th row	2016

Common Values

Value	Count	Frequency (%)
2016	84	42.2%
2017	82	41.2%
2018	22	11.1%
2019	8	4.0%
2020	3	1.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2016	84	42.2%
2017	82	41.2%
2018	22	11.1%
2019	8	4.0%
2020	3	1.5%

Most occurring characters

Value	Count	Frequency (%)
2	202	25.4%
0	202	25.4%
1	196	24.6%
6	84	10.6%
7	82	10.3%
8	22	2.8%
9	8	1.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	796	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
2	202	25.4%
0	202	25.4%
1	196	24.6%
6	84	10.6%
7	82	10.3%
8	22	2.8%
9	8	1.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	796	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
2	202	25.4%
0	202	25.4%
1	196	24.6%
6	84	10.6%
7	82	10.3%
8	22	2.8%
9	8	1.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	796	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
2	202	25.4%
0	202	25.4%
1	196	24.6%
6	84	10.6%
7	82	10.3%
8	22	2.8%
9	8	1.0%

cant_procesos_adjudicado
Real number (ℝ)

High correlation

Distinct	106
Distinct (%)	53.5%
Missing	1
Missing (%)	0.5%
Infinite	0
Infinite (%)	0.0%
Mean	112.86364

Minimum	1
Maximum	1214
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	8
median	30
Q3	111.75
95-th percentile	578.9
Maximum	1214
Range	1213
Interquartile range (IQR)	103.75

Descriptive statistics

Standard deviation	208.79209
Coefficient of variation (CV)	1.8499501
Kurtosis	10.14718
Mean	112.86364
Median Absolute Deviation (MAD)	27
Skewness	3.0988858
Sum	22347
Variance	43594.139
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
3	14	7.0%
1	9	4.5%
2	9	4.5%
5	7	3.5%
22	7	3.5%
13	6	3.0%
6	4	2.0%
8	4	2.0%
14	4	2.0%
44	3	1.5%
Other values (96)	131	65.8%

Value	Count	Frequency (%)
1	9	4.5%
2	9	4.5%
3	14	7.0%
4	3	1.5%
5	7	3.5%
6	4	2.0%
7	3	1.5%
8	4	2.0%
10	2	1.0%
11	2	1.0%

Value	Count	Frequency (%)
1214	1	0.5%
1102	1	0.5%
989	1	0.5%
895	1	0.5%
889	1	0.5%
864	1	0.5%
804	1	0.5%
792	1	0.5%
649	1	0.5%
635	1	0.5%

monto_total_adjudicado
Real number (ℝ)

High correlation

Distinct	198
Distinct (%)	100.0%
Missing	1
Missing (%)	0.5%
Infinite	0
Infinite (%)	0.0%
Mean	2.551944 × 10⁸

Minimum	6872
Maximum	6.9338191 × 10⁹
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	6872
5-th percentile	546768.44
Q1	7498428.6
median	35763034
Q3	1.9150669 × 10⁸
95-th percentile	8.0486084 × 10⁸
Maximum	6.9338191 × 10⁹
Range	6.9338122 × 10⁹
Interquartile range (IQR)	1.8400826 × 10⁸

Descriptive statistics

Standard deviation	7.6527844 × 10⁸
Coefficient of variation (CV)	2.9988058
Kurtosis	45.732919
Mean	2.551944 × 10⁸
Median Absolute Deviation (MAD)	34525936
Skewness	6.2881464
Sum	5.0528491 × 10¹⁰
Variance	5.8565109 × 10¹⁷
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
7425067.382	1	0.5%
27146231.22	1	0.5%
6933819091	1	0.5%
137988939	1	0.5%
3182253860	1	0.5%
7831100.398	1	0.5%
1375720032	1	0.5%
7242920.713	1	0.5%
86070142.1	1	0.5%
64475958.4	1	0.5%
Other values (188)	188	94.5%

Value	Count	Frequency (%)
6872	1	0.5%
23910.30243	1	0.5%
42000	1	0.5%
84943.48	1	0.5%
100200	1	0.5%
213056.6512	1	0.5%
240550.6182	1	0.5%
386494.5	1	0.5%
508479.1785	1	0.5%
533050.5125	1	0.5%

Value	Count	Frequency (%)
6933819091	1	0.5%
5903229493	1	0.5%
3182253860	1	0.5%
3132430594	1	0.5%
2548401882	1	0.5%
2252733473	1	0.5%
1375720032	1	0.5%
1375349531	1	0.5%
1005022056	1	0.5%
943321354.4	1	0.5%

antiguedad
Categorical

High correlation

Distinct	5
Distinct (%)	2.5%
Missing	0
Missing (%)	0.0%
Memory size	13.2 KiB

5.0	84
4.0	82
3.0	22
2.0	8
1.0	3

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	597
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	5.0
2nd row	5.0
3rd row	5.0
4th row	5.0
5th row	5.0

Common Values

Value	Count	Frequency (%)
5.0	84	42.2%
4.0	82	41.2%
3.0	22	11.1%
2.0	8	4.0%
1.0	3	1.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
5.0	84	42.2%
4.0	82	41.2%
3.0	22	11.1%
2.0	8	4.0%
1.0	3	1.5%

Most occurring characters

Value	Count	Frequency (%)
.	199	33.3%
0	199	33.3%
5	84	14.1%
4	82	13.7%
3	22	3.7%
2	8	1.3%
1	3	0.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	597	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	199	33.3%
0	199	33.3%
5	84	14.1%
4	82	13.7%
3	22	3.7%
2	8	1.3%
1	3	0.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	597	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	199	33.3%
0	199	33.3%
5	84	14.1%
4	82	13.7%
3	22	3.7%
2	8	1.3%
1	3	0.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	597	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	199	33.3%
0	199	33.3%
5	84	14.1%
4	82	13.7%
3	22	3.7%
2	8	1.3%
1	3	0.5%

provincia
Categorical

Imbalance

Distinct	13
Distinct (%)	6.5%
Missing	0
Missing (%)	0.0%
Memory size	23.8 KiB

Ciudad Autónoma de Buenos Aires	117
Buenos Aires	54
Santa Fe	7
Córdoba	7
San Juan	3
Other values (8)	11

Length

Max length	31
Median length	31
Mean length	22.61809
Min length	7

Characters and Unicode

Total characters	4501
Distinct characters	32
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	2.5%

Sample

1st row	Ciudad Autónoma de Buenos Aires
2nd row	Ciudad Autónoma de Buenos Aires
3rd row	Ciudad Autónoma de Buenos Aires
4th row	Buenos Aires
5th row	Ciudad Autónoma de Buenos Aires

Common Values

Value	Count	Frequency (%)
Ciudad Autónoma de Buenos Aires	117	58.8%
Buenos Aires	54	27.1%
Santa Fe	7	3.5%
Córdoba	7	3.5%
San Juan	3	1.5%
Corrientes	2	1.0%
San Luis	2	1.0%
Extranjera	2	1.0%
Rio Negro	1	0.5%
La Rioja	1	0.5%
Other values (3)	3	1.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
aires	171	23.2%
buenos	171	23.2%
ciudad	117	15.9%
de	117	15.9%
autónoma	117	15.9%
santa	7	1.0%
fe	7	1.0%
córdoba	7	1.0%
san	5	0.7%
juan	3	0.4%
Other values (11)	14	1.9%

Most occurring characters

Value	Count	Frequency (%)
	537	11.9%
e	475	10.6%
u	412	9.2%
d	359	8.0%
s	347	7.7%
n	310	6.9%
o	302	6.7%
i	295	6.6%
A	288	6.4%
a	270	6.0%
Other values (22)	906	20.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4501	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	537	11.9%
e	475	10.6%
u	412	9.2%
d	359	8.0%
s	347	7.7%
n	310	6.9%
o	302	6.7%
i	295	6.6%
A	288	6.4%
a	270	6.0%
Other values (22)	906	20.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4501	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	537	11.9%
e	475	10.6%
u	412	9.2%
d	359	8.0%
s	347	7.7%
n	310	6.9%
o	302	6.7%
i	295	6.6%
A	288	6.4%
a	270	6.0%
Other values (22)	906	20.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4501	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	537	11.9%
e	475	10.6%
u	412	9.2%
d	359	8.0%
s	347	7.7%
n	310	6.9%
o	302	6.7%
i	295	6.6%
A	288	6.4%
a	270	6.0%
Other values (22)	906	20.1%

cant_socios
Real number (ℝ)

Missing

Distinct	6
Distinct (%)	3.9%
Missing	45
Missing (%)	22.6%
Infinite	0
Infinite (%)	0.0%
Mean	1.9350649

Minimum	1
Maximum	8
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	2
95-th percentile	4
Maximum	8
Range	7
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.0269272
Coefficient of variation (CV)	0.53069391
Kurtosis	7.9885784
Mean	1.9350649
Median Absolute Deviation (MAD)	1
Skewness	2.1124298
Sum	298
Variance	1.0545794
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
2	72	36.2%
1	55	27.6%
3	16	8.0%
4	7	3.5%
5	3	1.5%
8	1	0.5%
(Missing)	45	22.6%

Value	Count	Frequency (%)
1	55	27.6%
2	72	36.2%
3	16	8.0%
4	7	3.5%
5	3	1.5%
8	1	0.5%

Value	Count	Frequency (%)
8	1	0.5%
5	3	1.5%
4	7	3.5%
3	16	8.0%
2	72	36.2%
1	55	27.6%

cant_apercibimientos
Categorical

High correlation Imbalance Missing

Distinct	3
Distinct (%)	2.1%
Missing	58
Missing (%)	29.1%
Memory size	13.0 KiB

1.0	131
2.0	9
3.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	423
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.7%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	131	65.8%
2.0	9	4.5%
3.0	1	0.5%
(Missing)	58	29.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	131	92.9%
2.0	9	6.4%
3.0	1	0.7%

Most occurring characters

Value	Count	Frequency (%)
.	141	33.3%
0	141	33.3%
1	131	31.0%
2	9	2.1%
3	1	0.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	423	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	141	33.3%
0	141	33.3%
1	131	31.0%
2	9	2.1%
3	1	0.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	423	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	141	33.3%
0	141	33.3%
1	131	31.0%
2	9	2.1%
3	1	0.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	423	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	141	33.3%
0	141	33.3%
1	131	31.0%
2	9	2.1%
3	1	0.2%

cant_suspensiones
Real number (ℝ)

High correlation Missing

Distinct	7
Distinct (%)	7.8%
Missing	109
Missing (%)	54.8%
Infinite	0
Infinite (%)	0.0%
Mean	2.0555556

Minimum	1
Maximum	7
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	2
95-th percentile	4
Maximum	7
Range	6
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.1549708
Coefficient of variation (CV)	0.56187769
Kurtosis	5.4527584
Mean	2.0555556
Median Absolute Deviation (MAD)	0
Skewness	2.0824203
Sum	185
Variance	1.3339576
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
2	48	24.1%
1	27	13.6%
3	6	3.0%
4	5	2.5%
6	2	1.0%
5	1	0.5%
7	1	0.5%
(Missing)	109	54.8%

Value	Count	Frequency (%)
1	27	13.6%
2	48	24.1%
3	6	3.0%
4	5	2.5%
5	1	0.5%
6	2	1.0%
7	1	0.5%

Value	Count	Frequency (%)
7	1	0.5%
6	2	1.0%
5	1	0.5%
4	5	2.5%
3	6	3.0%
2	48	24.1%
1	27	13.6%

cant_antecedentes
Real number (ℝ)

High correlation Missing

Distinct	8
Distinct (%)	4.1%
Missing	3
Missing (%)	1.5%
Infinite	0
Infinite (%)	0.0%
Mean	1.8163265

Minimum	1
Maximum	8
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	2
95-th percentile	4
Maximum	8
Range	7
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.2139948
Coefficient of variation (CV)	0.66837916
Kurtosis	6.1345897
Mean	1.8163265
Median Absolute Deviation (MAD)	0
Skewness	2.2516937
Sum	356
Variance	1.4737834
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
1	102	51.3%
2	62	31.2%
3	15	7.5%
4	8	4.0%
5	4	2.0%
6	3	1.5%
7	1	0.5%
8	1	0.5%
(Missing)	3	1.5%

Value	Count	Frequency (%)
1	102	51.3%
2	62	31.2%
3	15	7.5%
4	8	4.0%
5	4	2.0%
6	3	1.5%
7	1	0.5%
8	1	0.5%

Value	Count	Frequency (%)
8	1	0.5%
7	1	0.5%
6	3	1.5%
5	4	2.0%
4	8	4.0%
3	15	7.5%
2	62	31.2%
1	102	51.3%

cant_Apoderado
Real number (ℝ)

High correlation Missing

Distinct	6
Distinct (%)	4.2%
Missing	56
Missing (%)	28.1%
Infinite	0
Infinite (%)	0.0%
Mean	1.3146853

Minimum	1
Maximum	8
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	1
95-th percentile	3
Maximum	8
Range	7
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.88349164
Coefficient of variation (CV)	0.67201757
Kurtosis	25.573298
Mean	1.3146853
Median Absolute Deviation (MAD)	0
Skewness	4.4316866
Sum	188
Variance	0.78055747
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
1	117	58.8%
2	17	8.5%
3	4	2.0%
4	3	1.5%
8	1	0.5%
5	1	0.5%
(Missing)	56	28.1%

Value	Count	Frequency (%)
1	117	58.8%
2	17	8.5%
3	4	2.0%
4	3	1.5%
5	1	0.5%
8	1	0.5%

Value	Count	Frequency (%)
8	1	0.5%
5	1	0.5%
4	3	1.5%
3	4	2.0%
2	17	8.5%
1	117	58.8%

cant_representante
Categorical

High correlation Imbalance Missing

Distinct	3
Distinct (%)	3.2%
Missing	104
Missing (%)	52.3%
Memory size	12.8 KiB

1.0	81
2.0	13
3.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	285
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.1%

Sample

1st row	1.0
2nd row	2.0
3rd row	2.0
4th row	1.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
1.0	81	40.7%
2.0	13	6.5%
3.0	1	0.5%
(Missing)	104	52.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	81	85.3%
2.0	13	13.7%
3.0	1	1.1%

Most occurring characters

Value	Count	Frequency (%)
.	95	33.3%
0	95	33.3%
1	81	28.4%
2	13	4.6%
3	1	0.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	285	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	95	33.3%
0	95	33.3%
1	81	28.4%
2	13	4.6%
3	1	0.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	285	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	95	33.3%
0	95	33.3%
1	81	28.4%
2	13	4.6%
3	1	0.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	285	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	95	33.3%
0	95	33.3%
1	81	28.4%
2	13	4.6%
3	1	0.4%

cant_autenticado
Categorical

High correlation Imbalance

Distinct	5
Distinct (%)	2.5%
Missing	0
Missing (%)	0.0%
Memory size	13.2 KiB

1.0	166
2.0	28
3.0	3
4.0	1
5.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	597
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	1.0%

Sample

1st row	2.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
1.0	166	83.4%
2.0	28	14.1%
3.0	3	1.5%
4.0	1	0.5%
5.0	1	0.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	166	83.4%
2.0	28	14.1%
3.0	3	1.5%
4.0	1	0.5%
5.0	1	0.5%

Most occurring characters

Value	Count	Frequency (%)
.	199	33.3%
0	199	33.3%
1	166	27.8%
2	28	4.7%
3	3	0.5%
4	1	0.2%
5	1	0.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	597	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	199	33.3%
0	199	33.3%
1	166	27.8%
2	28	4.7%
3	3	0.5%
4	1	0.2%
5	1	0.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	597	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	199	33.3%
0	199	33.3%
1	166	27.8%
2	28	4.7%
3	3	0.5%
4	1	0.2%
5	1	0.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	597	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	199	33.3%
0	199	33.3%
1	166	27.8%
2	28	4.7%
3	3	0.5%
4	1	0.2%
5	1	0.2%

cant_noAutenticado
Categorical

High correlation Imbalance Missing

Distinct	5
Distinct (%)	12.5%
Missing	159
Missing (%)	79.9%
Memory size	12.6 KiB

1.0	31
2.0	5
3.0	2
7.0	1
4.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	120
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	5.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	2.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	31	15.6%
2.0	5	2.5%
3.0	2	1.0%
7.0	1	0.5%
4.0	1	0.5%
(Missing)	159	79.9%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	31	77.5%
2.0	5	12.5%
3.0	2	5.0%
7.0	1	2.5%
4.0	1	2.5%

Most occurring characters

Value	Count	Frequency (%)
.	40	33.3%
0	40	33.3%
1	31	25.8%
2	5	4.2%
3	2	1.7%
7	1	0.8%
4	1	0.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	120	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	40	33.3%
0	40	33.3%
1	31	25.8%
2	5	4.2%
3	2	1.7%
7	1	0.8%
4	1	0.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	120	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	40	33.3%
0	40	33.3%
1	31	25.8%
2	5	4.2%
3	2	1.7%
7	1	0.8%
4	1	0.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	120	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	40	33.3%
0	40	33.3%
1	31	25.8%
2	5	4.2%
3	2	1.7%
7	1	0.8%
4	1	0.8%

cant_sinMontoLimite
Real number (ℝ)

High correlation

Distinct	6
Distinct (%)	3.0%
Missing	1
Missing (%)	0.5%
Infinite	0
Infinite (%)	0.0%
Mean	1.469697

Minimum	1
Maximum	8
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	2
95-th percentile	3
Maximum	8
Range	7
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.92708314
Coefficient of variation (CV)	0.63079884
Kurtosis	14.896193
Mean	1.469697
Median Absolute Deviation (MAD)	0
Skewness	3.2557411
Sum	291
Variance	0.85948316
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
1	136	68.3%
2	47	23.6%
3	6	3.0%
4	5	2.5%
5	3	1.5%
8	1	0.5%
(Missing)	1	0.5%

Value	Count	Frequency (%)
1	136	68.3%
2	47	23.6%
3	6	3.0%
4	5	2.5%
5	3	1.5%
8	1	0.5%

Value	Count	Frequency (%)
8	1	0.5%
5	3	1.5%
4	5	2.5%
3	6	3.0%
2	47	23.6%
1	136	68.3%

cant_MontoLimite
Categorical

High correlation Missing

Distinct	2
Distinct (%)	33.3%
Missing	193
Missing (%)	97.0%
Memory size	12.5 KiB

1.0	5
2.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	18
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	16.7%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	5	2.5%
2.0	1	0.5%
(Missing)	193	97.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	5	83.3%
2.0	1	16.7%

Most occurring characters

Value	Count	Frequency (%)
.	6	33.3%
0	6	33.3%
1	5	27.8%
2	1	5.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	18	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	6	33.3%
0	6	33.3%
1	5	27.8%
2	1	5.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	18	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	6	33.3%
0	6	33.3%
1	5	27.8%
2	1	5.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	18	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	6	33.3%
0	6	33.3%
1	5	27.8%
2	1	5.6%

total_articulos_provee
Real number (ℝ)

High correlation

Distinct	147
Distinct (%)	73.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	412.94975

Minimum	1
Maximum	6661
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	1
5-th percentile	3
Q1	25
median	76
Q3	325
95-th percentile	2062.9
Maximum	6661
Range	6660
Interquartile range (IQR)	300

Descriptive statistics

Standard deviation	978.99978
Coefficient of variation (CV)	2.370748
Kurtosis	19.46077
Mean	412.94975
Median Absolute Deviation (MAD)	67
Skewness	4.1968645
Sum	82177
Variance	958440.56
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	7	3.5%
31	5	2.5%
5	5	2.5%
47	4	2.0%
3	4	2.0%
105	3	1.5%
30	3	1.5%
9	3	1.5%
16	3	1.5%
46	3	1.5%
Other values (137)	159	79.9%

Value	Count	Frequency (%)
1	7	3.5%
2	1	0.5%
3	4	2.0%
4	2	1.0%
5	5	2.5%
6	3	1.5%
7	2	1.0%
8	1	0.5%
9	3	1.5%
10	1	0.5%

Value	Count	Frequency (%)
6661	1	0.5%
6064	1	0.5%
5765	1	0.5%
3956	1	0.5%
3686	1	0.5%
3605	1	0.5%
3387	1	0.5%
3210	1	0.5%
3109	1	0.5%
2566	1	0.5%

cluster_k_4
Categorical

Constant

Distinct	1
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Memory size	12.8 KiB

2	199

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	199
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	2
3rd row	2
4th row	2
5th row	2

Common Values

Value	Count	Frequency (%)
2	199	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2	199	100.0%

Most occurring characters

Value	Count	Frequency (%)
2	199	100.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	199	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
2	199	100.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	199	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
2	199	100.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	199	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
2	199	100.0%

Interactions

Correlations

	Estado	TipoSocietario	anio_preinscripcion	antiguedad	cant_Apoderado	cant_MontoLimite	cant_antecedentes	cant_apercibimientos	cant_autenticado	cant_noAutenticado	cant_procesos_adjudicado	cant_representante	cant_sinMontoLimite	cant_socios	cant_suspensiones	monto_total_adjudicado	provincia	total_articulos_provee
Estado	1.000	0.363	0.176	0.176	0.000	1.000	0.024	0.000	0.230	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.354	0.000
TipoSocietario	0.363	1.000	0.311	0.311	0.000	0.000	0.062	0.000	0.000	0.000	0.000	0.071	0.053	0.082	0.000	0.431	0.390	0.000
anio_preinscripcion	0.176	0.311	1.000	1.000	0.000	0.000	0.069	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.327	0.000
antiguedad	0.176	0.311	1.000	1.000	0.000	0.000	0.069	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.327	0.000
cant_Apoderado	0.000	0.000	0.000	0.000	1.000	0.816	-0.070	0.000	0.459	0.714	-0.071	0.416	0.693	-0.003	-0.061	0.036	0.000	-0.186
cant_MontoLimite	1.000	0.000	0.000	0.000	0.816	1.000	0.866	1.000	0.000	0.000	0.000	1.000	0.000	0.000	1.000	1.000	0.000	1.000
cant_antecedentes	0.024	0.062	0.069	0.069	-0.070	0.866	1.000	0.334	0.014	0.000	-0.036	0.238	-0.118	-0.179	0.667	-0.168	0.276	0.158
cant_apercibimientos	0.000	0.000	0.000	0.000	0.000	1.000	0.334	1.000	0.000	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.171
cant_autenticado	0.230	0.000	0.000	0.000	0.459	0.000	0.014	0.000	1.000	0.000	0.000	0.498	0.547	0.000	0.000	0.000	0.186	0.000
cant_noAutenticado	0.000	0.000	0.000	0.000	0.714	0.000	0.000	1.000	0.000	1.000	0.000	0.000	0.678	0.495	0.882	0.364	0.000	0.000
cant_procesos_adjudicado	0.000	0.000	0.000	0.000	-0.071	0.000	-0.036	0.000	0.000	0.000	1.000	0.000	0.040	0.120	-0.364	0.665	0.000	0.423
cant_representante	0.000	0.071	0.000	0.000	0.416	1.000	0.238	0.000	0.498	0.000	0.000	1.000	0.412	0.144	0.491	0.000	0.000	0.093
cant_sinMontoLimite	0.000	0.053	0.000	0.000	0.693	0.000	-0.118	0.000	0.547	0.678	0.040	0.412	1.000	0.142	0.037	0.135	0.000	-0.144
cant_socios	0.000	0.082	0.000	0.000	-0.003	0.000	-0.179	0.000	0.000	0.495	0.120	0.144	0.142	1.000	-0.267	0.284	0.000	0.044
cant_suspensiones	0.000	0.000	0.000	0.000	-0.061	1.000	0.667	0.000	0.000	0.882	-0.364	0.491	0.037	-0.267	1.000	-0.397	0.351	0.034
monto_total_adjudicado	0.000	0.431	0.000	0.000	0.036	1.000	-0.168	0.000	0.000	0.364	0.665	0.000	0.135	0.284	-0.397	1.000	0.000	0.181
provincia	0.354	0.390	0.327	0.327	0.000	0.000	0.276	0.000	0.186	0.000	0.000	0.000	0.000	0.000	0.351	0.000	1.000	0.000
total_articulos_provee	0.000	0.000	0.000	0.000	-0.186	1.000	0.158	0.171	0.000	0.000	0.423	0.093	-0.144	0.044	0.034	0.181	0.000	1.000

Missing values

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

	CUIT	Nombre	FechaPreinscripcion	Estado	TipoSocietario	anio_preinscripcion	cant_procesos_adjudicado	monto_total_adjudicado	antiguedad	provincia	cant_socios	cant_apercibimientos	cant_suspensiones	cant_antecedentes	cant_Apoderado	cant_representante	cant_autenticado	cant_noAutenticado	cant_sinMontoLimite	cant_MontoLimite	total_articulos_provee	cluster_k_4
2	30711500363	LICICOM S.R.L.	15/09/2016	Inscripto	Sociedad Responsabilidad Limitada	2016	22.0	7.425067e+06	5.0	Ciudad Autónoma de Buenos Aires	2.0	1.0	2.0	4.0	2.0	1.0	2.0	1.0	3.0	NaN	105.0	2
23	30590151013	VIDITEC S.A..	22/07/2016	Inscripto	Sociedad Anónima	2016	47.0	2.714623e+07	5.0	Ciudad Autónoma de Buenos Aires	5.0	1.0	NaN	1.0	1.0	NaN	1.0	NaN	1.0	NaN	113.0	2
24	30678561165	NACION SEGUROS S.A.	15/11/2016	Inscripto	Sociedad Anónima	2016	1102.0	6.933819e+09	5.0	Ciudad Autónoma de Buenos Aires	5.0	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	26.0	2
29	30591267759	ERRE-DE SRL	02/08/2016	Inscripto	Sociedad Responsabilidad Limitada	2016	340.0	1.379889e+08	5.0	Buenos Aires	2.0	1.0	NaN	1.0	3.0	NaN	1.0	2.0	2.0	1.0	226.0	2
35	30702024834	Datastar Argentina S.A.	09/09/2016	Inscripto	Sociedad Anónima	2016	111.0	3.182254e+09	5.0	Ciudad Autónoma de Buenos Aires	2.0	1.0	NaN	1.0	2.0	2.0	2.0	2.0	4.0	NaN	207.0	2
39	30623295946	LAVIERI HNOS DE LAVIERI SEBASTIAN GABRIEL LAVIERI ALEJANDRO CARLOS.	29/09/2016	Inscripto	Sociedades De Hecho	2016	22.0	7.831100e+06	5.0	Ciudad Autónoma de Buenos Aires	2.0	1.0	NaN	1.0	NaN	2.0	2.0	NaN	2.0	NaN	37.0	2
60	30673249902	LOMAS DEL SOL SRL	21/10/2016	Suspendido	Sociedad Responsabilidad Limitada	2016	27.0	1.375720e+09	5.0	San Juan	2.0	NaN	4.0	4.0	1.0	NaN	1.0	NaN	1.0	NaN	602.0	2
85	30714236888	NANOTEC S.R.L.	30/09/2016	Inscripto	Sociedad Responsabilidad Limitada	2016	12.0	7.242921e+06	5.0	Ciudad Autónoma de Buenos Aires	2.0	1.0	NaN	1.0	1.0	NaN	1.0	NaN	1.0	NaN	160.0	2
89	30710362218	Licenciasonline SA	13/09/2016	Inscripto	Sociedad Anónima	2016	1.0	8.607014e+07	5.0	Ciudad Autónoma de Buenos Aires	4.0	1.0	NaN	1.0	1.0	1.0	1.0	1.0	2.0	NaN	3.0	2
103	30710828608	INFORMÁTICA PALMAR SRL	04/10/2016	Inscripto	Sociedad Responsabilidad Limitada	2016	143.0	6.447596e+07	5.0	Ciudad Autónoma de Buenos Aires	2.0	1.0	NaN	1.0	NaN	2.0	1.0	1.0	2.0	NaN	37.0	2

	CUIT	Nombre	FechaPreinscripcion	Estado	TipoSocietario	anio_preinscripcion	cant_procesos_adjudicado	monto_total_adjudicado	antiguedad	provincia	cant_socios	cant_apercibimientos	cant_suspensiones	cant_antecedentes	cant_Apoderado	cant_representante	cant_autenticado	cant_noAutenticado	cant_sinMontoLimite	cant_MontoLimite	total_articulos_provee	cluster_k_4
6894	20271824638	Albano Equipamientos	24/08/2018	Inscripto	Persona Física	2018	3.0	2.859164e+06	3.0	Buenos Aires	NaN	1.0	NaN	1.0	1.0	NaN	1.0	NaN	1.0	NaN	45.0	2
7046	30711958181	DEL BIANCO ELECTRONICA S.A.	13/03/2017	Inscripto	Sociedad Anónima	2017	3.0	2.405506e+05	4.0	Ciudad Autónoma de Buenos Aires	3.0	1.0	2.0	3.0	NaN	3.0	3.0	NaN	3.0	NaN	319.0	2
7387	30708351187	AR TECHNOLOGY S.R.L.	28/06/2018	Inscripto	Sociedad Responsabilidad Limitada	2018	5.0	8.783142e+06	3.0	Ciudad Autónoma de Buenos Aires	2.0	1.0	NaN	1.0	NaN	1.0	1.0	NaN	1.0	NaN	22.0	2
8150	30715995979	DESARROLLOS URBANOS RIO DE LA PLATA SRL	16/09/2020	Inscripto	Sociedad Responsabilidad Limitada	2020	18.0	2.095676e+08	1.0	Ciudad Autónoma de Buenos Aires	2.0	1.0	NaN	1.0	NaN	1.0	1.0	NaN	1.0	NaN	18.0	2
8165	30709585831	SECON SECURITY CONCEPT SA	11/04/2017	Inscripto	Sociedad Anónima	2017	1.0	1.326591e+07	4.0	Buenos Aires	2.0	1.0	NaN	1.0	1.0	1.0	1.0	1.0	1.0	1.0	102.0	2
8956	27181287077	FABIANA SANDRA CORTES	10/04/2017	Inscripto	Persona Física	2017	13.0	1.682270e+07	4.0	Buenos Aires	NaN	1.0	7.0	8.0	1.0	NaN	1.0	NaN	1.0	NaN	254.0	2
8957	A28006104	AIRBUS DEFENCE AND SPACE S.A.	21/06/2019	Pre Inscripto	Persona Jurídica Extranjero Sin Sucursal	2019	3.0	8.494348e+04	2.0	Extranjera	1.0	1.0	NaN	1.0	2.0	NaN	2.0	NaN	2.0	NaN	14.0	2
9237	214349010016	FARINTO S.A.	05/07/2019	Pre Inscripto	Persona Jurídica Extranjero Sin Sucursal	2019	NaN	NaN	2.0	Extranjera	1.0	1.0	NaN	1.0	1.0	NaN	1.0	NaN	1.0	NaN	6.0	2
9504	30716582082	BATERIAS ECOBAT S.A.S	16/10/2020	Inscripto	Otras Formas Societarias	2020	1.0	8.288520e+05	1.0	San Juan	1.0	1.0	NaN	1.0	NaN	1.0	1.0	NaN	1.0	NaN	1.0	2
9783	30707835563	SUTEL S.R.L.	25/08/2016	Inscripto	Sociedad Responsabilidad Limitada	2016	2.0	3.889114e+06	5.0	Buenos Aires	2.0	NaN	2.0	2.0	NaN	1.0	1.0	NaN	1.0	NaN	329.0	2

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)